Multi-Robot Task Allocation in Lunar Mission Construction Scenarios
George Thomas, Ayanna Howard, Andrew B. Williams, A. Moore-Alston
- 发表年份
- 2006
- 引用次数
- 16
摘要
In this paper, we propose a method for multi-robot task allocation based on the concept of task decomposition for a lunar mission scenario. This methodology focuses on segmenting a task scenario into a sequence of operations called functional primitives that are defined a priori by a set of performance metrics and resource requirements. In real-time, multiple robotic agents determine their capabilities and skill sets associated with the defined functional primitives in order to determine a suitable allocation scheme. We discuss the methodology in detail and provide results for a simulated lunar mission construction scenario using the Multi-Agent Robot Simulator for Lunar Construction (MARS-LC) system.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002